SBM-RGBD Challenge @ RGBD2017

The aim of the SBM-RGBD Challenge, organized in conjunction with the Workshop on Background Learning for Detection and Tracking from RGBD Videos (RGBD2017, ), is to evaluate and compare scene background modelling methods for moving object detection on RGBD videos of the (updated on July 13th, 2017).
Researchers from both academia and industry are invited to test their moving object detection algorithms on the and to report their results in order to participate to the Challenge (see Instructions below). Results from all submissions that meet certain minimum quality standards will be reported and maintained in the webpage.


The winners are the authors of the SCAD algorithm, described in the paper: T. Minematsu, A. Shimada, H. Uchiyama and R.-i. Taniguchi, Simple Combination of Appearance and Depth for Foreground Segmentation, in S. Battiato, G. Gallo, G.M. Farinella, M. Leo (Eds), New Trends in Image Analysis and Processing-ICIAP 2017 Workshops, Lecture Notes in Computer Science, Springer, 2017.

Deadline to submit results

The Challenge is now closed, but you can still submit your results with the below procedure to be added into the webpage.

Instructions for prospective participants

Challenge organizers

, University of Bristol, UK
, National Research Council, Italy
, Universitat de les Illes Balears, Spain
, University of Naples Parthenope, Italy
, Universidad Politecnica de Madrid & Universidad Autonoma de Madrid, Spain